Optical Imaging Demonstrates Tissue-Specific Metabolic Perturbations in Mblac1 Knockout Mice.

OBJECTIVE: Metabolic changes have been extensively documented in neurodegenerative brain disorders, including Parkinson's disease and Alzheimer's disease (AD). Mutations in the C. elegans swip-10 gene result in dopamine (DA) dependent motor dysfunction accompanied by DA neuron degeneration. Recently, the putative human ortholog of swip-10 (MBLAC1) was implicated as a risk factor in AD, a disorder that, like PD, has been associated with mitochondrial dysfunction. Interestingly, the AD risk associated with MBLAC1 arises in subjects with cardiovascular morbidity, suggesting a broader functional insult arising from reduced MBLAC1 protein expression and one possibly linked to metabolic alterations. METHODS: Our current studies, utilizing Mblac1 knockout (KO) mice, seek to determine whether mitochondrial respiration is affected in the peripheral tissues of these mice. We quantified the levels of mitochondrial coenzymes, NADH, FAD, and their redox ratio (NADH/FAD, RR) in livers and kidneys of wild-type (WT) mice and their homozygous KO littermates of males and females, using 3D optical cryo-imaging. RESULTS: Compared to WT, the RR of livers from KO mice was significantly reduced, without an apparent sex effect, driven predominantly by significantly lower NADH levels. In contrast, no genotype and sex differences were observed in kidney samples. Serum analyses of WT and KO mice revealed significantly elevated glucose levels in young and aged KO adults and diminished cholesterol levels in the aged KOs, consistent with liver dysfunction. DISCUSSION/CONCLUSION: As seen with C. elegans swip-10 mutants, loss of MBLAC1 protein results in metabolic changes that are not restricted to neural cells and are consistent with the presence of peripheral comorbidities accompanying neurodegenerative disease in cases where MBLAC1 expression changes impact risk.

Demonstrating drug treatment efficacies by monitoring superoxide dynamics in human lung cancer cells with time-lapse fluorescence microscopy.

Metformin hydrochloride, an antihyperglycemic agent, and sulindac, a nonsteroidal anti-inflammatory drug, are FDA-approved drugs known to exert anticancer effects. Previous studies demonstrated sulindac and metformin's anticancer properties through mitochondrial dysfunction and inhibition of mitochondrial electron transport chain complex I and key signaling pathways. In this study, various drugs were administered to A549 lung cancer cells, and results revealed that a combination of sulindac and metformin enhanced cell death compared to the administration of the drugs separately. To measure superoxide production over time, we employed a time-lapse fluorescence imaging technique using mitochondrial-targeted hydroethidine. Fluorescence microscopy data showed the most significant increases in superoxide production in the combination treatment of metformin and sulindac. Results showed significant differences between the combined drug treatment and control groups and between the positive control and control groups. This approach can be utilized to quantify the anticancer efficacy of drugs, creating possibilities for additional therapeutic options.

Optical Imaging Reveals Liver Metabolic Perturbations in Mblac1 Knockout Mice.

Metabolic changes have been extensively documented in brain tissue undergoing neurodegeneration, including Parkinson's disease and Alzheimer's disease (AD). Mutations in the C. elegans swip-10 gene result in dopamine (DA) dependent motor dysfunction accompanied by DA neuron degeneration. Recently, the putative human ortholog of swip-10 (MBLAC1) was implicated as a risk factor in AD, that like PD, has been associated with mitochondrial dysfunction. Interestingly, the AD risk associated with MBLAC1 arises in subjects with cardiovascular morbidity, suggesting the possibility of a broader functional insult arising from reduced MBLAC1 protein expression, and one possibly linked to metabolic alterations. Our current studies, utilizing Mblac1 knockout (KO) mice, seeks to determine whether mitochondrial respiration is affected in peripheral tissues of these animals in this model. To initiate these studies, we quantified the levels of mitochondrial coenzymes, NADH, FAD, and their redox ratio (NADH/FAD, RR) in the livers of wild type (WT) mice and their homozygous KO littermates, using 3D optical cryo-imaging. We found that Mblac1 KO mice exhibited a greater oxidized redox state compared to WT mice. When compared to the WT group, the redox ratio of KO mice was decreased by 46.32%, driven predominantly by significantly lower NADH levels (more oxidized state). We speculate that, as seen with C. elegans swip-10 mutants, that loss of MBLAC1 protein results in deficits in tricarboxylic acid cycle (TCA) production of NADH and FAD TCA that leads to diminished cellular ATP production and oxidative stress. Such observations are consistent with changes that in the central nervous system (CNS) could support neurodegeneration and in the periphery account for comorbidities.

Comparing Steady-State Visually Evoked Potentials Frequency Estimation Methods in Brain-Computer Interface With the Minimum Number of EEG Channels.

INTRODUCTION: Brain-Computer Interface (BCI) systems provide a communication pathway between users and systems. BCI systems based on Steady-State Visually Evoked Potentials (SSVEP) are widely used in recent decades. Different feature extraction methods have been introduced in the literature to estimate SSVEP responses to BCI applications. METHODS: In this study, the new algorithms, including Canonical Correlation Analysis (CCA), Least Absolute Shrinkage and Selection Operator (LASSO), L1-regularized Multi-way CCA (L1-MCCA), Multi-set CCA (MsetCCA), Common Feature Analysis (CFA), and Multiple Logistic Regression (MLR) are compared using proper statistical methods to determine which one has better performance with the least number of EEG electrodes. RESULTS: It was found that MLR, MsetCCA, and CFA algorithms provided the highest performances and significantly outperformed CCA, LASSO, and L1-MCCA algorithms when using 8 EEG channels. However, when using only 1 or 2 EEG channels d, CFA method provided the highest F-scores. This algorithm not only outperformed MLR and MsetCCA when applied on different electrode montages but also provided the fastest computation time on the test set. CONCLUSION: Although MLR method has already demonstrated to have higher performance in comparison with other frequency recognition algorithms, this study showed that in a practical SSVEP-based BCI system with 1 or 2 EEG channels and short-time windows, CFA method outperforms other algorithms. Therefore, it is proposed that CFA algorithm is a promising choice for the expansion of practical SSVEP-based BCI systems.